Papers with DCCE framework

1 papers
A Robust Dual-debiasing VQA Model based on Counterfactual Causal Effect (2024.findings-emnlp)

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Challenge: Existing VQA models suffer from language bias that indicates a spurious correlation between textual questions and answers.
Approach: They propose a model agnostic dual-debiasing framework that models two types of language bias by separate branches under counterfactual inference framework.
Outcome: The proposed framework significantly reduces language bias and achieves state-of-the-art performance on the benchmark datasets.

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